Due to the privacy reasons, there is no publicly available dataset for cyberattack detection, therefore, we generate a synthetic dataset.
As a first step, for each \(t\)  in \(1 \le t \le 36000\) , we scale load and generation values of each bus in the 2848-bus test system [1]} by a uniform random value between 0.8 and 1.2; run AC power flow algorithms [2]}; and save power measurements after adding 1% noise to them to mimic the timely behavior of the grid.
Then, to simulate the cyberattacks, we implement data scale attacks (\(A_s\) ) [3]} and distribution-based attacks (\(A_d\) ) [4]} as of two frequently used cyberattack generation algorithms.
Scale attacks multiply the original measurement with a number sampled from a uniform distribution between 0.9 and 1.1.
In contrast, distribution-based attacks replace it with a value drawn from the Gaussian distribution satisfying the same mean and variance with the original measurements.
